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I think that fMRI is just beginning to realize its potential. It is such a powerful technique to image the brain, that as we improve the technique and can see more, we will learn more. I like to make the analogy that modern imaging techniques (MRI, microscopy, PET, etc.) have done at least as much to expand human knowledge as the more widely known (within the general public) telescopes (Hubble, JWST, etc.).
One thing that I like about this approach is that it is looking at the brain as a complex system rather than trying to ID and characterize individual neurons. From the article:
This reminds me of my statistical mechanics course when I was in grad school. You can study individual particles all you want, but when you get a large number of them, things change. One oxygen molecule behaves differently than a room full of air just like a single neuron behaves differently than a head filled with a brain. The path of neuroscience is following a similar trajectory physics did in that it could make sense of things at the individual scale, but working with large numbers of interactions is harder and requires more complex experiments/theories/models to deal with.
Totally, like if you were an alien trying to study a computer, you can look at an individual transistor all you want but at some point you need to look at how all the different complex network systems work together to make a software program.
The language of computer programming has worked it's way more and more even into clinical neurology. I talk about motor programs for instance when trying to explain dystonias, where the brain activates a set of movement patterns that's not at all what the person was trying to do. You might find functional neurologic disorders interesting. Super common problem that needs a lot more research. Many patients have trouble grasping the idea of a "software" problem in the brain so don't talk about it and don't realize just how common it is. Fmri has started to help uncover the abberant patterns that lead to these disorders.